Data Platform Engineer

About Upstart

Upstart is a leading AI lending marketplace partnering with banks and credit unions to expand access to affordable credit. By leveraging Upstart's AI marketplace, Upstart-powered banks and credit unions can have higher approval rates and lower loss rates across races, ages, and genders, while simultaneously delivering the exceptional digital-first lending experience their customers demand. More than two-thirds of Upstart loans are approved instantly and are fully automated.

Upstart is a digital-first company, which means that most Upstarters live and work anywhere in the United States. However, we also have offices in San Mateo, California; Columbus, Ohio; and Austin, Texas.

Most Upstarters join us because they connect with our mission of enabling access to effortless credit based on true risk. If you are energized by the impact you can make at Upstart, we’d love to hear from you!

The Data Platform Engineering team (Part of Upstart's core platform vertical) provides developer tools, frameworks, and scalable data infrastructure as shared services across Upstart. The team's primary objective is to provide Data Analysts, Software Engineers, and ML scientists access to high-quality data and developer tools to create business metrics for respective product verticals. 

You will join the subdivision focusing on Data Curation. 

As the Data Platform Engineer joining this team, you will get the opportunity to contribute to following areas:

1. Build and maintain user-friendly, scalable tools that enable data teams and other stakeholders to perform data transformations without needing deep technical expertise.
2. Expand the self-serve ETL and orchestration framework that developers use to build pipelines
3. Manage, organize, and maintain the data catalog to ensure efficient data discovery, governance, access control, and metadata management across the organization.

We would love to hear from you if you are passionate about building data products!

How you’ll make an impact:

• Build and Improve the tools owned by the Data Curation team
• Participate in planning and prioritization by collaborating with stakeholders across the various product verticals and functions (ML, Analytics, Finance, Software engineering) to ensure our tools/frameworks help deliver overall business objectives.
• Collaborate with stakeholders such as Software Engineering, Machine Learning, Machine Learning Platform and Analytics teams to onboard them to the Lakehouse and adopt the developer tools 
• Participate in code reviews and architecture discussions to exchange actionable feedback with peers. 
• Help break down complex projects and requirements into stories for sprints.
• Continuously monitor and improve data platform performance, reliability, and security.
• Stay up-to-date with emerging technologies and industry best practices in data engineering.
• Develop and maintain technical documentation for the data platform, including design, architecture, and operational procedures. Promote best practices for data engineering within the organization.

What we’re looking for: 

• Minimum requirements:
  • A bachelor's degree in Computer Science, Data Science, Engineering, or a related field.
  • 3+ years of experience in data platform development, data engineering or related fields
  • Proficiency in data engineering tech stack; Databricks / PostgreSQL / Python / Spark / Kafka / SQL / AWS / Airflow/ DBT / containers and orchestration (Docker, Kubernetes) and others.
  • Ability to approach problems with first principles thinking, embrace ambiguity, and enjoy collaborative work on complex solutions. 
• Preferred qualifications:
  • Strong foundation in algorithms and data structures and their real-world use cases.
  • Strong analytical and troubleshooting skills, with the ability to analyze complex technical challenges and deliver effective solutions.
  • Experience and understanding of distributed systems, data architecture design, and big data technologies (e.g., Spark, Kafka, Lakehouse, Databricks).
  • Experience with AWS technologies ( e.g.,  AWS Lambda, Redshift, RDS, S3, etc.).
  • Good knowledge of DevOps engineering using Continuous Integration/Delivery tools like Kubernetes, Jenkins, Terraform, etc., thinking about automation, alerting, monitoring, security, and other declarative infrastructure.
  • Ability to explain complex concepts in easy-to-understand ways and navigate environments where problems are not well-defined (and evolve quickly).

Position Location - This role is available in the following locations: Remote, San Mateo, Columbus 

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